1. Light-level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds.

Over the next century, climate change will dramatically alter natural resource management. Specifically, historical reference conditions may no longer serve as benchmarks for restoration, which may foster a "why bother?" attitude toward ecological restoration. We review the potential role for riparian restoration to prepare ecological systems for the threats posed by climate change. Riparian ecosystems are naturally resilient, provide linear habitat connectivity, link aquatic and terrestrial ecosystems, and create thermal refugia for wildlife: all characteristics that can contribute to ecological adaptation to climate change. Because riparian systems and the projected impacts of climate change are highly variable geographically, there is a pressing need to develop a place-based understanding of climate change threats to riparian ecosystems. Restoration practitioners should consider how they can modify practices to enhance the resilience of riparian ecosystems to climate change. Such modifications may include accelerating the restoration of private lands, participating in water management decisions, and putting the emerging field of restoration genetics into practice.

Conservationists must develop new strategies and adapt existing tools to address the consequences of anthropogenic climate change. To support statewide climate change adaptation, we developed a framework for assessing climate change vulnerability of California's at-risk birds and integrating it into the existing California Bird Species of Special Concern list. We defined climate vulnerability as the amount of evidence that climate change will negatively impact a population. We quantified climate vulnerability by scoring sensitivity (intrinsic characteristics of an organism that make it vulnerable) and exposure (the magnitude of climate change expected) for each taxon. Using the combined sensitivity and exposure scores as an index, we ranked 358 avian taxa, and classified 128 as vulnerable to climate change. Birds associated with wetlands had the largest representation on the list relative to other habitat groups. Of the 29 state or federally listed taxa, 21 were also classified as climate vulnerable, further raising their conservation concern. Integrating climate vulnerability and California's Bird Species of Special Concern list resulted in the addition of five taxa and an increase in priority rank for ten. Our process illustrates a simple, immediate action that can be taken to inform climate change adaptation strategies for wildlife.

Using mist nets, we compared phyllostomid bat ensembles of continuous mature forest in Tikal National Park, Guatemala, and of forest fragments in the nearby farming landscape. Of 20 species captured, 13 were shared between treatments, 4 were unique to continuous forest, and 3 were unique to forest fragments. Dominance–diversity curves were similar for the two treatments except that Sturnira lilium comprised 43 percent of captures in the forest fragments, resulting in greater dominance there. Capture rates (and presumably relative abundance) differed significantly between continuous forest and forest fragments, both in terms of species and feeding guilds. Sturnia lilium and Dermanura sp. were captured significantly more often in forest fragments than in continuous forest, whereas Artibeus jamaicensis, A. lituratus, and Centurio senex were taken significantly more often in continuous forest. Large frugivores accounted for a higher proportion of total captures in continuous forest than in forest fragments, whereas small frugivores showed the opposite pattern. By their abundances, Carollia perspicillata and S. lilium are indicators of forest disturbance. The relative abundances of large frugivores, which feed on large fruits of mature forest trees, and small frugivores, which feed on small‐fruited plants occurring in early succession, are an indicator of forest disturbance. Other groups, such as large insect‐ and vertebrate‐eating bats, because of their low capture rates, are impractical as indicators for rapid assessment of forest disturbance based on mist netting, but may prove especially vulnerable to forest fragmentation.

BackgroundSolar archival tags (henceforth called geolocators) are tracking devices deployed on animals to reconstruct their long-distance movements on the basis of locations inferred post hoc with reference to the geographical and seasonal variations in the timing and speeds of sunrise and sunset. The increased use of geolocators has created a need for analytical tools to produce accurate and objective estimates of migration routes that are explicit in their uncertainty about the position estimates.ResultsWe developed a hidden Markov chain model for the analysis of geolocator data. This model estimates tracks for animals with complex migratory behaviour by combining: (1) a shading-insensitive, template-fit physical model, (2) an uncorrelated random walk movement model that includes migratory and sedentary behavioural states, and (3) spatially explicit behavioural masks.The model is implemented in a specially developed open source R package FLightR. We used the particle filter (PF) algorithm to provide relatively fast model posterior computation. We illustrate our modelling approach with analysis of simulated data for stationary tags and of real tracks of both a tree swallow Tachycineta bicolor migrating along the east and a golden-crowned sparrow Zonotrichia atricapilla migrating along the west coast of North America.ConclusionsWe provide a model that increases accuracy in analyses of noisy data and movements of animals with complicated migration behaviour. It provides posterior distributions for the positions of animals, their behavioural states (e.g., migrating or sedentary), and distance and direction of movement.Our approach allows biologists to estimate locations of animals with complex migratory behaviour based on raw light data. This model advances the current methods for estimating migration tracks from solar geolocation, and will benefit a fast-growing number of tracking studies with this technology.